Razvan Pascanu

According to our database1, Razvan Pascanu authored at least 69 papers between 2010 and 2018.

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Bibliography

2018
Meta-Learning with Latent Embedding Optimization.
CoRR, 2018

Relational Deep Reinforcement Learning.
CoRR, 2018

Relational recurrent neural networks.
CoRR, 2018

Mix&Match - Agent Curricula for Reinforcement Learning.
CoRR, 2018

Relational inductive biases, deep learning, and graph networks.
CoRR, 2018

Hyperbolic Attention Networks.
CoRR, 2018

Been There, Done That: Meta-Learning with Episodic Recall.
CoRR, 2018

Progress & Compress: A scalable framework for continual learning.
CoRR, 2018

Low-pass Recurrent Neural Networks - A memory architecture for longer-term correlation discovery.
CoRR, 2018

Block Mean Approximation for Efficient Second Order Optimization.
CoRR, 2018

Learning Deep Generative Models of Graphs.
CoRR, 2018

Memory-based Parameter Adaptation.
CoRR, 2018

Model compression via distillation and quantization.
CoRR, 2018

Progress & Compress: A scalable framework for continual learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Been There, Done That: Meta-Learning with Episodic Recall.
Proceedings of the 35th International Conference on Machine Learning, 2018

Mix & Match Agent Curricula for Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Imagination-Augmented Agents for Deep Reinforcement Learning.
CoRR, 2017

Visual Interaction Networks.
CoRR, 2017

Distral: Robust Multitask Reinforcement Learning.
CoRR, 2017

A simple neural network module for relational reasoning.
CoRR, 2017

Discovering objects and their relations from entangled scene representations.
CoRR, 2017

Learning model-based planning from scratch.
CoRR, 2017

Metacontrol for Adaptive Imagination-Based Optimization.
CoRR, 2017

Sharp Minima Can Generalize For Deep Nets.
CoRR, 2017

Sobolev Training for Neural Networks.
CoRR, 2017

Visual Interaction Networks: Learning a Physics Simulator from Video.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Distral: Robust multitask reinforcement learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A simple neural network module for relational reasoning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sobolev Training for Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sharp Minima Can Generalize For Deep Nets.
Proceedings of the 34th International Conference on Machine Learning, 2017

Sim-to-Real Robot Learning from Pixels with Progressive Nets.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2016
Local minima in training of deep networks.
CoRR, 2016

Sim-to-Real Robot Learning from Pixels with Progressive Nets.
CoRR, 2016

Progressive Neural Networks.
CoRR, 2016

Learning to Navigate in Complex Environments.
CoRR, 2016

Overcoming catastrophic forgetting in neural networks.
CoRR, 2016

Interaction Networks for Learning about Objects, Relations and Physics.
CoRR, 2016

Theano: A Python framework for fast computation of mathematical expressions.
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CoRR, 2016

Interaction Networks for Learning about Objects, Relations and Physics.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Policy Distillation.
CoRR, 2015

Natural Neural Networks.
CoRR, 2015

Natural Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Malware classification with recurrent networks.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014
On the saddle point problem for non-convex optimization.
CoRR, 2014

On the Number of Linear Regions of Deep Neural Networks.
CoRR, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.
CoRR, 2014

Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

On the Number of Linear Regions of Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Natural Gradient Revisited
CoRR, 2013

Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines
CoRR, 2013

On the number of inference regions of deep feed forward networks with piece-wise linear activations.
CoRR, 2013

How to Construct Deep Recurrent Neural Networks.
CoRR, 2013

Learned-norm pooling for deep neural networks.
CoRR, 2013

Pylearn2: a machine learning research library.
CoRR, 2013

On the difficulty of training recurrent neural networks.
Proceedings of the 30th International Conference on Machine Learning, 2013


Advances in optimizing recurrent networks.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Learning Algorithms for the Classification Restricted Boltzmann Machine.
Journal of Machine Learning Research, 2012

Advances in Optimizing Recurrent Networks
CoRR, 2012

Theano: new features and speed improvements
CoRR, 2012

Understanding the exploding gradient problem
CoRR, 2012

2011
Contextual tag inference.
TOMCCAP, 2011

A neurodynamical model for working memory.
Neural Networks, 2011

Deep Learners Benefit More from Out-of-Distribution Examples.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Autotagging music with conditional restricted Boltzmann machines
CoRR, 2011

2010
Deep Self-Taught Learning for Handwritten Character Recognition
CoRR, 2010

Extraction of quadrics from noisy point-clouds using a sensor noise model.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010


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